Active aluminum window-frame integrated prototype with a thermoelectric heat recovery system for ventilation and air conditioning
Bibliographic record
Abstract
Research interest in the integration of thermoelectric systems in the building envelope have increased during the last years. Studies show that regardless of a low COP compared to vapor compression systems; thermoelectric systems present other remarkable features for heating, cooling and ventilation on buildings. Among those studies, a few prototype experiences incorporate thermoelectric systems on windows.Alternatively, standard air conditioning systems often require additional equipment installed on façade or wall surfaces that compromise the use of space in the case of building refurbishment. Thus, the integration of thermoelectric systems on window framing is presented here as a decentralized alternative for air conditioning support, whose performance aims at balancing out the heat losses in windows. The purpose of this communication is to present the development of an active aluminum window-framing prototype with a thermoelectric heat recovery system for heating and cooling. In a typical single-floor house scenario, the active window-frame works in two different modes: pre heating/cooling mode applying forced convection through a mechanical fan and pre heating/cooling mode with natural convection. The impulsion airflow rate meets ventilation requirements according to Spanish Technical Building Code (CTE) for indoor air quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".